Webinar Recap: Do I Have A Big Data Problem?

Most companies today still make business decisions based on guesses, hunches and intuition rather than leverage data-driven analytics platforms. Many don’t understand how to capture the insights or they don’t have the mathematical expertise to make their data meaningful in a manner that helps describe what they should look for. As companies transition away from traditional ways of doing business and start capturing the relevant data that allows senior management to make informed decisions, they encounter an explosion of data growth that legacy database systems and information management processes can no longer manage.

In our experience, one question that comes up a lot is: What can I do with all this new information? Knowing that you’re encountering problems with your legacy database licensing and performance, we facetiously asked participants in our latest webinar to consider this question: “Do I have a Big Data problem?” The answer yes – anyone with a dataset that is unmanageable does indeed have a Big Data problem.

One problem companies face is that they do a great job of creating data, but they don’t often know how to get value from the data they are creating. For example:

Online retailers want to look at users’ buying patterns and interests so that they can make the right shopping recommendations to customers

Manufacturing lines and just-in-time companies need to understand flow and delays in production lines

Auto manufacturers yearn to understand when, why and how car parts break; which helps designers make changes and improve their designs.

And Big Data is not just about predictive analytics; it’s also about getting the right information to the right people. The best way to get to the right information is to ask the right questions for defining the outcome of business analytics. These questions include:

What are the most important business questions that you don’t have answers for?

What are you trying to get out of that predictive crystal ball that we all wish that we had?

Once you have analyzed the data, how do you organize your company to be able to react to the results that come from Big Data analytics?

In our webinar, we addressed what Big Data breaks within IT and businesses; offered considerations on what to select for a Big Data platform; talked to the common data patterns that we hear from our customers; explained what is needed to make those patterns meaningful; and then explained the three most common pitfalls that companies fall into when beginning their journey to Big Data-driven decisions and data analytics.

Before you watch this webinar (here), we want to remind you that Big Data means different things to different companies and industries. We welcome the opportunity to answer any questions that you have on Big Data in general or how Rackspace and its partners can help you. Please feel free to reach out to us at KParker@rackspace.com and Matt.Richins@rackspace.com.

About the Author

This is a post written and contributed by
Matt Richins and Kevin Parker.

Matt Richins has over 20 years of IT experience working with companies across all of North and South America; including several top fortune 500 companies within the manufacturing, retail, services, banking, and media and entertainment industries. Over those years, he has specialized in Big Data as an architect of global WANs, large scale application infrastructures, and disaster recovery solutions for petabyte+ data replication and restoral, and virtualized and cloud solutions. As a technologist, he has developed an extensive knowledge base of the hardware and software aspects that support telecommunications, application development and deployment, cloud computing, automation, virtualization, and server architectures

In his role at Rackspace, Matt is focused on helping companies to adopt cloud and automation technologies that allow them to boost efficiencies of application performance while reclaiming IT operations time to focus it on deploying new business enabling technologies and also allowing them to work closer with the business units to help meet their technology needs.

Kevin Parker is an Architect within Rackspace’s Enterprise Cloud Solutions organization and develops complex cloud infrastructures for his clientele. As a tenured member of the Rackspace team, Kevin is a Senior Advisor to the company’s Enterprise Sales and Product organizations. Having 12-plus years in the IT industry, he has a deep understanding of the challenges facing the enterprise. Kevin develops strategies to optimize application availability, performance and scalability, as well as essential solutions focused on business continuity, disaster recovery, storage efficiency, information security, and deployment strategy. Kevin holds a B.S. in both Biochemistry and Biology from Trinity University where his research in Immunology provided him a deep understanding of complex adaptive systems.